Smooth Granular Sound Texture Synthesis by Control of Timbral Similarity

Autor: Schwarz, Diemo, O 'leary, Sean
Přispěvatelé: Interaction Son Musique Mouvement [Paris], Sciences et Technologies de la Musique et du Son (STMS), Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Analyse et synthèse sonores, PHYSIS, ANR-12-CORD-0006,PHYSIS,Modèles de synthèse audio interactifs, physiquement informé et sémantiquement contrôlables.(2012), Schwarz, Diemo, Contenus et Interactions - Modèles de synthèse audio interactifs, physiquement informé et sémantiquement contrôlables. - - PHYSIS2012 - ANR-12-CORD-0006 - CONTINT - VALID
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: 12th Sound and Music Computing Conference
Sound and Music Computing (SMC)
Sound and Music Computing (SMC), Jul 2015, Maynooth, Ireland. pp.6
www.maynoothuniversity.ie/smc15/
Popis: International audience; Granular methods to synthesise environmental sound textures (e.g. rain, wind, fire, traffic, crowds) preserve the richness and nuances of actual recordings, but need a preselection of timbrally stable source excerpts to avoid unnaturally-sounding jumps in sound character. To overcome this limitation, we add a description of the timbral content of each sound grain to choose successive grains from similar regions of the timbre space. We define two different timbre similarity measures, one based on perceptual sound descriptors, and one based on MFCCs. A listening test compared these two distances to an uncon-strained random grain choice as baseline and showed that the descriptor-based distance was rated as most natural, the MFCC based distance generally as less natural, and the random selection always worst.
Databáze: OpenAIRE
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